Implementing Clustering Based Approach for Evaluation of Success of Software Reuse using K-means algorithm

Authors

  • Jagmeet Kaur RBCEBTW
  • Dr. Dheerendra Singh SUSCET

DOI:

https://doi.org/10.24297/ijct.v4i3.4199

Keywords:

Kmeans, Reuse and Machine learning.

Abstract

A great deal of research over the past several years has been devoted to the development of methodologies to create reusable software components and component libraries. But the issue of how to find the contribution of the factor towards the successfulness of the reuse program is still in the naïve stage and very less work is done on the modeling of the success of the reuse. The success and failure factors are the key factors that predict the successful reuse of software. An algorithm has been proposed in which the inputs can be given to K-Means Clustering system in form of tuned values of the Data Factors and the developed model shows the high precision results , which describe the success of software reuse.

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Author Biographies

Jagmeet Kaur, RBCEBTW

Assistant Professor, CSE/IT

Dr. Dheerendra Singh, SUSCET

Professor and HOD, CSE

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Published

2013-04-30

How to Cite

Kaur, J., & Singh, D. D. (2013). Implementing Clustering Based Approach for Evaluation of Success of Software Reuse using K-means algorithm. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 4(3), 807–812. https://doi.org/10.24297/ijct.v4i3.4199

Issue

Section

Research Articles